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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Application of GRNN for the prediction of performance and exhaust emissions in HCCI engine using ethanol
Harisankar Bendu, B. B. V. L. Deepak, S. Murugan
Energy Conversion and Management (2016) Vol. 122, pp. 165-173
Closed Access | Times Cited: 111

Showing 1-25 of 111 citing articles:

Prediction of maximum surface settlement caused by earth pressure balance (EPB) shield tunneling with ANN methods
Renpeng Chen, Pin Zhang, Xin Kang, et al.
SOILS AND FOUNDATIONS (2019) Vol. 59, Iss. 2, pp. 284-295
Open Access | Times Cited: 216
Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions
Masoud Aliramezani, Charles Robert Koch, Mahdi Shahbakhti
Progress in Energy and Combustion Science (2021) Vol. 88, pp. 100967-100967
Closed Access | Times Cited: 190
Prediction of shield tunneling-induced ground settlement using machine learning techniques
Renpeng Chen, Pin Zhang, Huai-Na Wu, et al.
Frontiers of Structural and Civil Engineering (2019) Vol. 13, Iss. 6, pp. 1363-1378
Closed Access | Times Cited: 157
Review of artificial neural networks for gasoline, diesel and homogeneous charge compression ignition engine
Ibham Veza, Asif Afzal, M.A. Mujtaba, et al.
Alexandria Engineering Journal (2022) Vol. 61, Iss. 11, pp. 8363-8391
Open Access | Times Cited: 127
Multi-objective optimization of ethanol fuelled HCCI engine performance using hybrid GRNN–PSO
Harisankar Bendu, B. B. V. L. Deepak, S. Murugan
Applied Energy (2016) Vol. 187, pp. 601-611
Closed Access | Times Cited: 117
Prediction and optimization of surface roughness and micro-hardness using grnn and MOORA-fuzzy-a MCDM approach for nitinol in WEDM
Himadri Majumder, Kalipada Maity
Measurement (2018) Vol. 118, pp. 1-13
Closed Access | Times Cited: 117
Effect of bioethanol on combustion and emissions in advanced CI engines: HCCI, PPC and GCI mode – A review
Hyun Kwon Noh, Soo-Young No
Applied Energy (2017) Vol. 208, pp. 782-802
Closed Access | Times Cited: 115
Risk prediction and factors risk analysis based on IFOA-GRNN and apriori algorithms: Application of artificial intelligence in accident prevention
Xuecai Xie, Gui Fu, Yujingyang Xue, et al.
Process Safety and Environmental Protection (2018) Vol. 122, pp. 169-184
Closed Access | Times Cited: 106
Developing a model to predict the start of combustion in HCCI engine using ANN-GA approach
Mahmood Taghavi, Ayat Gharehghani, Firooz Bakhtiari-Nejad, et al.
Energy Conversion and Management (2019) Vol. 195, pp. 57-69
Closed Access | Times Cited: 98
Investigation on the ignition delay prediction model of multi-component surrogates based on back propagation (BP) neural network
Yanqing Cui, Haifeng Liu, Qianlong Wang, et al.
Combustion and Flame (2021) Vol. 237, pp. 111852-111852
Closed Access | Times Cited: 73
A data-driven roadmap for creep-fatigue reliability assessment and its implementation in low-pressure turbine disk at elevated temperatures
Run‐Zi Wang, Hang-Hang Gu, Shun‐Peng Zhu, et al.
Reliability Engineering & System Safety (2022) Vol. 225, pp. 108523-108523
Open Access | Times Cited: 67
Machine learning assisted probabilistic creep-fatigue damage assessment
Hang-Hang Gu, Run‐Zi Wang, Shun‐Peng Zhu, et al.
International Journal of Fatigue (2021) Vol. 156, pp. 106677-106677
Closed Access | Times Cited: 63
Combustion enhancement and emission reduction in an IC engine by adopting ZnO nanoparticles with calophyllum biodiesel/diesel/propanol blend: A case study of General Regression Neural Network (GRNN) modelling
M. Srinivasarao, Ch. Srinivasarao, Aneeta Kumari, et al.
Industrial Crops and Products (2025) Vol. 227, pp. 120812-120812
Open Access | Times Cited: 1
Mahua seed pyrolysis oil blends as an alternative fuel for light-duty diesel engines
Debalaxmi Pradhan, Harisankar Bendu, Rajat Singh, et al.
Energy (2016) Vol. 118, pp. 600-612
Closed Access | Times Cited: 85
Application of GRNN and multivariate hybrid approach to predict and optimize WEDM responses for Ni-Ti shape memory alloy
Himadri Majumder, Kalipada Maity
Applied Soft Computing (2018) Vol. 70, pp. 665-679
Closed Access | Times Cited: 73
Numerical and Experimental Investigation of Ethyl Alcohol as Oxygenator on the Combustion, Performance, and Emission Characteristics of Diesel/Cotton Seed Oil Blends in Homogenous Charge Compression Ignition Engine
Medhat Elkelawy, Hagar Alm‐Eldin Bastawissi, Saravanan Sekar, et al.
SAE technical papers on CD-ROM/SAE technical paper series (2018)
Closed Access | Times Cited: 72
A data-driven evolutionary algorithm for wind farm layout optimization
Huan Long, Peikun Li, Wei Gu
Energy (2020) Vol. 208, pp. 118310-118310
Closed Access | Times Cited: 56
Machine learning model for prediction of drug solubility in supercritical solvent: Modeling and experimental validation
Feifei An, Biju Theruvil Sayed, Rosario Mireya Romero‐Parra, et al.
Journal of Molecular Liquids (2022) Vol. 363, pp. 119901-119901
Closed Access | Times Cited: 30
Effects of biodiesel-ethanol-diesel blends on the performance indicators of a diesel engine: A study by response surface modeling
Golmohammad Khoobbakht, Mahmoud Karimi, Kamran Kheiralipour
Applied Thermal Engineering (2018) Vol. 148, pp. 1385-1394
Closed Access | Times Cited: 58
Improving the lean performance of an n-butanol rotary engine by hydrogen enrichment
Teng Su, Changwei Ji, Shuofeng Wang, et al.
Energy Conversion and Management (2017) Vol. 157, pp. 96-102
Closed Access | Times Cited: 54
Predictive Analysis on Responses in WEDM of Titanium Grade 6 Using General Regression Neural Network (GRNN) and Multiple Regression Analysis (MRA)
Himadri Majumder, Kalipada Maity
Silicon (2018) Vol. 10, Iss. 4, pp. 1763-1776
Closed Access | Times Cited: 50
Optimization and matching for range-extenders of electric vehicles with artificial neural network and genetic algorithm
Jinxing Zhao, Yingying Ma, Zhendong Zhang, et al.
Energy Conversion and Management (2019) Vol. 184, pp. 709-725
Closed Access | Times Cited: 50
Prediction of Wear Characteristics of AA2219-Gr Matrix Composites Using GRNN and Taguchi-Based Approach
A. Saravanakumar, L. Rajeshkumar, D. Balaji, et al.
Arabian Journal for Science and Engineering (2020) Vol. 45, Iss. 11, pp. 9549-9557
Closed Access | Times Cited: 42
Development of a new reduced hydrogen combustion mechanism with NOx and parametric study of hydrogen HCCI combustion using stochastic reactor model
Rakesh Kumar Maurya, Akhil Nekkanti
Energy Conversion and Management (2016) Vol. 132, pp. 65-81
Closed Access | Times Cited: 43
An experimental investigation on combustion, performance and ringing operation characteristics of a low compression ratio early direct injection HCCI engine with ethanol fuel blends
Seyfi Polat
Fuel (2020) Vol. 277, pp. 118092-118092
Closed Access | Times Cited: 36
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